AMBER alert monitoring and support

ABSTRACT

Embodiments are disclosed for responding to an incoming alert using vehicle resources to scan and report on an environment of a vehicle. An example an in-vehicle computing system of a vehicle includes a sensor subsystem in communication with a sensor, a communication interface, a processor, and memory storing instructions executable by the processor to receive, via the communication interface, an alert including one or more alert parameters, instruct the sensor to scan an assigned region around the vehicle, receive, from the sensor, locally scanned data corresponding to the assigned region, determine that the scanned data includes an object having features matching a selected alert parameter of the one or more alert parameters, and transmit, to an alert service, a notification identifying the object and the features matching the selected alert parameter, the notification including a location of the object.

FIELD

The disclosure relates to automatically responding to emergency alertsin a vehicle.

BACKGROUND

Vehicles may be equipped with cameras or other sensing devices to detectsurroundings of the vehicles. For example, a vehicle may include aplurality of cameras or other sensors around a perimeter of the vehicle(e.g., on different sides of the vehicle, on a front of the vehicle, ona rear of the vehicle, etc.) to capture a view of a road on which thevehicle is traveling, neighboring vehicles, and/or other objects nearthe vehicle.

In-vehicle computing systems and/or devices connected to the vehicle(e.g., mobile devices of occupants) may be connected to communicationservices that provide emergency alerts, such as emergency weatheralerts, emergency traffic alerts, and America's Missing: BroadcastEmergency Response (AMBER) alerts. Received alerts may include detailsfor recipients to respond to the alert. For example, AMBER alerts mayinclude information regarding a person or vehicle of interest that maybe involved in suspect activity.

SUMMARY

Vehicle operators may be targets for emergency alerts such as AMBERalerts, as travelling vehicles may cover large areas and therebyeffectively expand a region that may be scanned for suspiciousactivities, vehicles, and/or people. However, tasking a civilian driverof a vehicle with visually scanning for suspects may distract the driverfrom vehicle operating tasks. Even if the driver does not perform thevisual scanning, the initial presentation of the alert may be anadditional source of distraction.

The disclosure provides an automated vehicle-based system that processesincoming alerts (e.g., incoming AMBER alerts), utilizes vehicle sensorsto scan and identify environmental objects or people that matchinformation in the alerts, and transmits the identified information to athird party (e.g., a law enforcement agency). An example in-vehiclecomputing system includes a sensor subsystem in communication with asensor, a communication interface, a processor, and memory storinginstructions executable by the processor to receive, via thecommunication interface, an alert including one or more alertparameters, instruct the sensor to scan an assigned region around thevehicle, receive, from the sensor, locally scanned data corresponding tothe assigned region, determine that the scanned data includes an objecthaving features matching a selected alert parameter of the one or morealert parameters, and transmit, to an alert service, a notificationidentifying the object and the features matching the selected alertparameter, the notification including a location of the object.

An example method for responding to an incoming alert with an automaticalert processing system of a vehicle includes scanning an assignedregion around a vehicle for an object matching one or more alertparameters of the incoming alert, the one or more alert parametersdescribing one or more target objects, and transmitting, to an alertservice, a notification indicating a location of a found object thatmatches at least a selected parameter of the one or more alertparameters of the incoming alert, the notification including aconfidence score indicating a likelihood that the found object matchesone or more target objects of the incoming alert.

Another example in-vehicle computing system includes a sensor subsystemin communication with an optical sensor, a communication interface, aprocessor, and memory storing instructions executable by the processorto receive, via the communication interface, an alert including one ormore alert parameters associated with one or more target objects,instruct the optical sensor to scan a first assigned region around thevehicle, and determine, using a first set of processing resources, thatscanned data corresponding to the first assigned region includes anobject having features matching a selected alert parameter of the one ormore alert parameters. The instructions are also executable to instructthe optical sensor to scan a second assigned region around the vehicle,the second assigned region being smaller than the first assigned regionand targeting the object, determine, using a second set of processingresources analyzing scanned data corresponding to the second assignedregion, that the object has additional features matching one or moreadditional alert parameters of the one or more alert parameters, andtransmit, to an alert service, a notification identifying the object andeach of the features matching each associated alert parameter of the oneor more alert parameters, the notification including a location of theobject.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may be better understood from reading the followingdescription of non-limiting embodiments, with reference to the attacheddrawings, wherein below:

FIGS. 1A-1C show an example alert distribution and vehicle response inaccordance with one or more embodiments of the present disclosure;

FIG. 2 shows a block diagram of an example automatic alert processingsystem and an associated example processing flow in accordance with oneor more embodiments of the present disclosure;

FIG. 3 shows a flow chart of an example method for automaticallyprocessing an emergency alert in accordance with one or more embodimentsof the present disclosure;

FIG. 4 shows a flow chart of an example method for group-basedprocessing of an emergency alert in accordance with one or moreembodiments of the present disclosure;

FIG. 5 is a flow chart of an example method for distributing computingloads responsive to receipt of an emergency alert in accordance with oneor more embodiments of the present disclosure;

FIG. 6 shows an example partial view of a vehicle cabin in accordancewith one or more embodiments of the present disclosure; and

FIG. 7 shows a block diagram of an in-vehicle computing system inaccordance with one or more embodiments of the present disclosure.

DETAILED DESCRIPTION

Emergency alerts, such as AMBER alerts, may be transmitted to the publicto provide the public with a description of individuals, vehicles,and/or other details related to an emergency situation. For example,AMBER alerts may include a description of a suspect, an individual indanger, and a vehicle associated with the suspect/individual. Aby-stander or driver that receives the alert may act as the “eyes andears” of law enforcement to provide valuable tips regarding a locationof the suspect/individual, which may lead to the apprehension of thesuspect.

For a driver, an incoming alert may serve as a distraction, as thedriver listens to or reads the alert, and if the driver attempts toidentify whether anything or anyone in the environment matches thedescriptions provided in the alert. Furthermore, the driver may onlyhave a single vantage point from the vehicle (e.g., from the driver'sseat of the vehicle) and may be dividing his/her attention betweendriving tasks and viewing the environment to identify informationrelevant to the alert. Accordingly, the driver may not identify suchinformation with a high level of accuracy and/or efficiency.

The systems and methods provided in the disclosure minimize driverdistraction resulting from incoming alerts, and increases efficiency andaccuracy of responding to received alerts. For example, the systems andmethods may include the use of cameras or other sensors located invarious regions of a vehicle to scan a large area of the environmentaround the vehicle and identify features that are relevant to a receivedalert (e.g., a suspect/individual matching a description in the alert, avehicle/license plate matching a description in the alert, etc.). Thesensors of the vehicle that identify the relevant features (and/or othersensors working in coordination) may also identify additional detailsidentifying a status of the recognized features (e.g., a headingdirection and speed of a vehicle matching the description in the alert)and capture real-time imagery of the recognized features. The additionalinformation may be transmitted to a third party, such as a lawenforcement agency, for further review. The law enforcement agency mayuse captured information from multiple automatic alert processingsystems in multiple vehicles to help locate a person or vehicle ofinterest. As will be discussed further, vehicles may also utilizevehicle-to-vehicle communication to coordinate scanning and responses toreceived alerts.

It is to be understood that the disclosure may refer to an AMBER alertas an example of an emergency alert that may be responded to moreefficiently through the use of the disclosed automatic alert processingmethods and systems. However, the efficiency of the disclosed automaticalert processing methods and systems may also benefit other types ofemergency alerts. Accordingly, description herein that is directedtoward AMBER alerts and associated data may likewise be applied to anyother type of emergency alerts and associated data without departingfrom the scope of the disclosure.

FIGS. 1A-1C illustrate an example alert environment 100 for a group ofvehicles that may receive an emergency alert, such as an AMBER alert.Environment 100 includes a portion of a roadway 102, on which vehicles104 a, 104 b, 104 c, and 104 d are travelling, and a portion of asidewalk 103, on which pedestrians 105 a and 105 b are walking. Eachvehicle may be communicatively connected to and/or otherwise able toreceive data from a network 106. For example, network 106 may include orrepresent a cellular network, a radio broadcast system, an ad hoc localnetwork (e.g., created between groups of vehicles), and/or any otherwireless network or data transmission system. Network 106 may beindividually connected to each vehicle in some examples. In additionalor alternative examples, network 106 may broadcast information across abroadcast range (e.g., from one or more transmission points), such thatany vehicle with a compatible data receiver within the broadcast rangeof the network may receive the broadcast information.

Network 106 may be communicatively coupled to alert source 108 andconfigured to receive alert data from alert source 108. Alert source 108may include or be further communicatively coupled to an authority suchas a law enforcement agency or other associated computing system. Forexample, an alert may be generated at alert source 108 including datafrom the law enforcement agency regarding information identifying asuspect and/or an individual in danger (e.g., height, weight, haircolor, clothing, distinctive markings, etc.) and/or informationidentifying vehicles associated with the suspect or individual (e.g.,make, model, year, color, license plate number, etc.). As shown in FIG.1A, the alert generated at alert source 108 may be provided ortransmitted to network 106 for distribution to the vehicles 104 a-104 d(and/or other devices within a broadcast range of network 106, forexample). In some examples, the alert source 108 may be included in ormay form the network 106, such that the alert is transmitted orbroadcast to the vehicles and/or other devices from the same computingsystem that generated the alert using data from the law enforcementagency.

FIG. 1B shows an example response to the alert from vehicle 104 b. It isto be understood that, while only one vehicle is shown responding in theexample of FIG. 1B for illustrative purposes, any vehicle that includesan automatic alert processing system may respond to the alert in asimilar manner to vehicle 104 b. As shown, a response to the alert mayinclude performing an automated scan for information regarding objectsin a vicinity of the vehicle that received the alert. In the illustratedexample, vehicle 104 b is shown detecting objects in a scan region 110in front of the vehicle. In other examples (or at a later time period inthe illustrated example), any or all of the sensors on vehicle 104 b maybe used to scan an environment of the vehicle (e.g., side cameras tocover left and right side scan regions and rear cameras to cover a rearscan region). An automatic alert processing system of vehicle 104 b mayengage any front-facing cameras or other scanning devices in the vehicleto begin scanning for vehicles or individuals that match informationprovided in a received alert. In some examples, each engaged scanningdevice may continuously scan the environment simultaneously. In otherexamples, at least some of the scanning devices may scan the environmentin periodic and/or alternating shifts.

In the illustrated example, the scan region 110 includes individual 105b and at least portions of vehicles 104 c and 104 d. Accordingly, theautomatic alert processing system of vehicle 104 b may analyze data fromthe scanning devices covering the scan region 110 (e.g., front cameras)to identify the individuals and vehicles and compare features of theindividuals and vehicles to information from the received alert. Forexample, once individual 105 b is identified as an individual,characteristics such as hair color, clothing, and size of the individualmay be compared to information in the alert to identify any matches.Likewise, once vehicles 104 c and 104 d are identified as vehicles,characteristics such as make/model, color, and license plate of thevehicles may be compared to information in the alert to identify anymatches. In this way, at least some different characteristics may beevaluated for different classes of objects (e.g., vehicle-targetedcharacteristics versus individual-targeted characteristics). It is to beunderstood that evaluating a vehicle may also include evaluatingindividual-targeted characteristics of any individuals inside thevehicle. In some examples, only characteristics that are described inthe alert are examined (e.g., if the alert identifies a hair color ofthe individual but not the clothing of the individual, only hair colorof individual 105 b, and not clothing, may be evaluated by the automaticalert processing system of vehicle 104 b). In other examples, allcharacteristics of an individual or vehicle may be evaluated, but onlycharacteristics that are described in the alert are identified forcomparison to the alert.

FIG. 1C shows an example response to performing the scanning operationin scan region 110. As illustrated, vehicle 104 b may communicate withthe alert source 108 or associated system (e.g., a law enforcementcomputing system) directly or via network 106 to provide informationregarding the scanning operation. For example, if one or more ofindividual 105 b, vehicle 104 c, and vehicle 104 d include features thatmatch information from the received alert, vehicle 104 b may transmitinformation regarding that individual and/or vehicle(s), the matchedfeatures, the location of the individual/vehicle(s), and/or any otherassociated information to the law enforcement agency or other computingsystem (e.g., the alert may identify a computing system to whichresponses to the alert are to be sent). In some examples, the responseto the alert is sent to the same system that generated the alert (e.g.,the alert source 108). In other examples, the response to the alert issent to a different system (e.g., a third-party receiver incommunication with appropriate authorities to filter or otherwiseprocess the responses).

FIG. 2 shows an example block diagram of an automatic alert processingsystem 200 and an example processing flow between components of theautomatic alert processing system. The automatic alert processing system200 may be included in any suitable vehicle, including but not limitedto the vehicles of FIGS. 1A-1C (e.g., vehicle 104 b). The automaticalert processing system 200 includes a communication interface 202 thatis configured to receive emergency alerts (e.g., AMBER alerts) from oneor more alert systems. For example, communication interface 202 may be ahardware interface including or coupled to physical receivers ortransceivers (e.g., antennas) to connect the automatic alert processingsystem 200 to one or more radio transmitters/transceivers, cellularnetworks, over-the-air (OTA) broadcast transmitters, local data links(e.g., vehicle-to-vehicle communication links, mobile phone-to-vehiclecommunication links, etc.), and/or other communication links ornetworks. The communication interface 202 may receive emergency alertsover any one or combination of the above-described communicationnetworks/links. For example, the communication interface 202 may receivean alert via a radio transmission (e.g., embedded in radio broadcastsaccording to the Radio Data System [RDS] or similar protocol, XFM datachannels, specialized mobile radio service [SMRs], etc.), via an SMStext-based system (e.g., directly or through a local data link with amobile device of a driver or other vehicle occupant), and/or via acellular broadcast (e.g., according to the Wireless Emergency Alertprogram or Commercial Mobile Alert System). It is to be understood thatalerts may also be received by the system in other manners, such as viauser input and/or detected via vehicle scanning devices (e.g., animaging device that captures an image of a billboard or other roadsidesign with an AMBER alert printed or displayed thereon). In someexamples, different alert sources may include different amounts andtypes of information for the same alert. Accordingly, some alerts may beprocessed in coordination with one another (e.g., whereby multiplealerts received from different sources but relating to the samesuspect/individual in danger may be processed together) and alerts maybe processed differently based on which path the alert travels (e.g.,between the alert source and the vehicle). For example, scanning regionsand/or alert parameters that are selected for matching scanned data maybe selected based on a data path from which the alert is received.

Received alerts are passed to an alert processing unit 204, which may beimplemented via a processor executing instructions stored in a storagedevice (e.g., memory). The alert processing unit 204 may include one ormore parsing modules 206 and data extraction modules 208 for formattingand/or interpreting the data of the received alerts. For example, alertsmay include text data indicating a description of one or more suspects,individuals in danger, and associated vehicles. The parsing modules 206may recognize a context of the textual information (e.g., which portionsof text relate to an individual in danger, which relate to a suspect,which relate to a vehicle, etc.). The extraction modules may extractparameters of the alert from the textual information (e.g., “red shirt,”“brown hair,” “123 456”) for association with a vehicle or persondescribed in the alert (e.g., “red shirt” is associated with a suspect,“brown hair” is associated with an individual in danger, and “123 456”is associated with a license plate of a vehicle). In this way, the alertprocessing unit 204 may provide parameters for matching detected objectsin an environment with descriptions included in a received alert.

Once the alert is received and/or processed by processing unit 204, theprocessing unit may instruct a scanning control unit 210 to initiate ascan via a scan initiation request. The scanning control unit 210 mayinclude and/or control one or more cameras 212 (e.g., vehicle camerasthat are mounted on the vehicle and/or cameras of a device that isconnected to the vehicle, such as a mobile phone camera), microphones214, and/or other scanners 216 (e.g., optical scanners such as LiDARscanners, electromagnetic scanners such as radar scanners, and/orsound-based scanners such as sonar scanners). The scanning control unit210 may select one or more of the associated scanners based on a contentof the alert (e.g., if all of the information in the alert isvisually-based, the scanning control unit 210 may instruct only opticalcameras/scanners to perform scans of the environment of the vehicle). Insome examples, targeted areas of the scans may be based on the contentof the alert and/or information from other sources regarding the alert.For example, the alert processing system 200 may receive notice fromanother vehicle (e.g., via the communication interface 202) that ascanned vehicle matching the suspect vehicle identified in the alert wasidentified at a first location and headed east toward the vehicle inwhich alert processing system 200 is included. In response, the scanningcontrol unit 210 may instruct only cameras on the west side of thevehicle to scan for the suspect vehicle, since the suspect vehicle islikely to be approaching from that direction. Targeting the scan in thismanner may conserve resources and reduce false positive recognitions,resulting in a more efficient and accurate scanning process compared toscans utilize all available scanning devices.

In other examples, all available scanning devices may be used in orderto cover a larger area than a targeted scan. Such wide-range scanexamples may increase the number of alert-matching features that aredetected during scanning relative to the above-described targetedscanning, since a larger region of coverage provides more candidates formatching features. The wide-range scan may be utilized when a targetedvehicle or suspect is erratic and/or is otherwise not likely to follow alogic path toward the vehicle performing the scan.

The scan data from a scanning operation may be sent to a scan dataprocessing unit 218 along with the alert parameters derived from thealert processing unit 204. For example, the scan data may include rawdata output from one or more of the above-described scanning devices(e.g., images from cameras 212, audio from microphones 214, depthimaging data or other scan data from other scanners 216, etc.). The scandata processing unit 218 may include one or more modules for analyzingthe received scan data, extracting features for comparison to alertparameters received from alert processing unit 204, and determiningwhether the extracted features match the alert parameters. For example,the scan data processing unit 218 may include a license plate matchingmodule 220 for performing object recognition on the scan data toidentify a license plate in the environment and text/characterrecognition on the scan data to recognize an identifier of the licenseplate (e.g., a license plate number and/or state/province/municipality)for matching a target license plate identifier included in the alertparameters.

The scan data processing unit 218 may also include a vehicle matchingmodule 222 for recognizing vehicles in the scan data (e.g., performingobject recognition to identify vehicles or vehicle components),determining features of recognized vehicles, and determining if featuresof the recognized vehicles match alert parameters from the alertprocessing unit 204. Similarly, a person matching module 224 of the scandata processing unit may recognize individuals in the scan data (e.g.,performing object recognition to identify humans or human body parts),determining features of the recognized individuals, and determining ifthe features of the recognized individuals match alert parameters fromthe alert processing unit 204.

A vehicle and/or person status detection module 226 may also be includedin the scan data processing unit 218. The vehicle and/or person statusdetection module may detect additional contextual information regardingvehicles and/or individuals identified as matching one or more of thealert parameters. For example, the vehicle and/or person statusdetection module may utilize scan data and/or data from other sensors todetermine a heading, speed of movement, and/or other state of a vehicleor individual that matches the alert parameter(s). For example, avehicle matching an alert parameter may be parked with a flat tire.Providing information regarding not only the location of the vehicle butalso the parked with flat tire status may help authorities attempting tolocate a suspect associated with the vehicle (e.g., by identifying thatthe suspect likely abandoned the vehicle and is now in a differentvehicle).

The information gathered and analyzed with the scan data processing unit218 may be provided to the communication interface 202 for transmissionto a third party system that handles incoming alert responses and/or alaw enforcement agency or other associated authority. As illustrated,the automatic alert processing system may optionally include an outputinterface 228 for providing, to a user, information regarding the alertand/or the analyzed scan data matching alert parameters. For example,the output interface 228 may be coupled to an in-vehicle display orother output device for notifying a driver or other occupant ofinformation relevant to the alert. The automatic alert processing systemmay also optionally include a user input interface 230 for receivingdata from a user input device (e.g., a touch screen in the vehicle or amicrophone in the vehicle) relating to the alert.

For example, a user may (e.g., after receiving information regarding thealert via the output interface 228) recognize a vehicle or individualmatching a parameter of the alert and provide an indication of thisrecognition to the automatic alert processing system for transmission tothe third party system that handles incoming alert responses. In anotherexample, a user may (e.g., after receiving information regarding thevehicle/individual matching the alert parameters according to the scandata processing unit 218) provide additional details regarding thematched vehicle/individual (e.g., a status of the vehicle/individual, asdiscussed above) and/or confirm or refute/edit the findings of the scandata processing unit. In this way, an overall distraction of the usermay be reduced while still allowing the user to contribute to the alertresponse. Furthermore, the user input interface may enable passengerswho are not preoccupied with driving tasks assist the automatic alertprocessing system by providing the above-described user inputs toenhance the output of the scan data processing unit 218. The numberand/or type of alert parameters displayed on the output interface 228,when employed, may be kept to a minimum (e.g., color, make, and model ofthe car, gender of the driver, etc.) in order to minimize thedistraction provided to the driver. In some examples, the alertparameters may only be provided to an output device that is directed toa passenger and/or to a separate mobile device of a passenger in orderto avoid distracting the driver. If a user finds a match to one of thefew parameters displayed, the user may provide the indication of thematch to the system in order to direct the system to scan and processadditional information about the target identified by the user. In thisway, the user input regarding the alert may be provided to an alertservice and/or may be used to further control the automatic processingof the alert by the vehicle.

FIG. 3 is a flow chart of an example method 300 for automaticallyprocessing an emergency alert using an automatic alert processing system(e.g., alert processing system 200 of FIG. 2). At 302, the methodincludes receiving an alert (e.g., an alert indicating a suspect,individual in danger, and/or other person of interest and/or associatedvehicle). At 304, the method includes verifying the alert source and/ordata in the alert. For example, a blockchain may be used to validateinformation arriving at a vehicle as authentic. Additional oralternative authentication schemes may be used to secure communicationsbetween the vehicle and an alert source, including security protocolsbuilt into the communication protocol utilized by the vehicle and alertsource (e.g., Internet Protocol [IP], BLUETOOTH, WIFI) and suitableencryption (e.g., prefix-preserving encryption [PPE]).

At 306, the method includes identifying the alert parameters (e.g., foralerts that are verified at 304). For example, alert parameters mayinclude types of objects for which the vehicle is to scan (e.g., personsof interest, vehicles, etc.) and features of the objects for which thevehicle is to scan (e.g., appearance of persons/vehicles—such as hair,clothing, height, weight, age, race, and tattoos/scars of persons andcolor, make, model, year, license plate, accessories, and condition ofvehicles). Other information included in the alert may provideparameters to target scanning, such as a last knownlocation/heading/speed or an expected location of the objects for whichthe vehicle is to scan.

At 308, the method includes scanning a first region of an environmentaround a vehicle using one or more scanning devices (e.g., 2D and/or3D/depth cameras). The first region may refer to an area relative to thevehicle (e.g., a cone in front of the vehicle, an area around thecircumference of the vehicle radiating outward a particular distancefrom the vehicle, etc.). In some examples, the first region may be afull range of operation (e.g., field of view and/or range in whichobjects are able to be detected) of the one or more scanning devicesused for scanning. In other examples, the first region may be a subsetof the full range of operation of the one or more scanning devices (or,where two or more scanning devices are used, the first region may be afull range of operation of a subset of the two or more scanning devicesthat are used for scanning).

At 310, the method includes determining if an object and/or personhaving features matching the alert parameters is detected. If an objectand/or person having features matching the alert parameters is notdetected (e.g., “NO” at 310), the method proceeds to 312 to store anindication that a matching object/person is not present in the scannedregion. The indication may be timestamped in order to track changes tothis determination. The method further proceeds to 314 to scan a nextregion. In examples where the first region represents the full operationrange of the one or more scanning devices used to scan the environment,the next region may be the same region (relative to the vehicle) at adifferent point in time (e.g., at a different range of world locationsthan the first region if the vehicle is moving). After scanning the nextregion, the method returns to 310 to determine if an object/personhaving features matching the alert parameters is detected. The methodmay be exited if the vehicle leaves a range of coverage of the alertwithout detecting the object/person of interest for at least a thresholdperiod of time.

If an object/person having features that match the alert parameters isdetected (e.g., “YES” at 310), the method proceeds to 316 and includesgathering additional contextual information regarding the object and/orperson having features that match the alert parameters. For example, thelocation (e.g., geotag), time of recognition (e.g., timestamp), heading,speed, percentage of match, terrain, neighboring vehicles/landmarks,and/or other contextual information for the matching object and/orperson may be determined using the scanning devices and/or othersensors/devices of the vehicle. At 318, the method includes transmittingan identification of the object and/or person having features that matchthe alert parameters and the additional contextual information to analert service. The alert service may be a central computing system towhich responses to a given alert may be transmitted for analysis. Thealert service may aggregate data from the responses in order to verifypotential detections of an object and/or person(s) of interest and passalong information from the alert responses to associated authorities.

The driver and/or other occupants of the vehicle may provide user inputto set user preferences controlling the manner in which data is sharedwith the alert service. For example, a user may provide privacy settingscontrolling an amount of information about the driver/vehicle that isprovided to the alert service with an alert response. In some examples,a user may select an option to remain anonymous when sending an alertresponse. In other examples, a user may select an option to provide aphone number or other contact information when sending an alert responseto enable the alert service or authorities associated with the alertcontact the user to request further information. User preferences mayalso be set to control in which alert systems the user wishes toparticipate (e.g., AMBER alerts, stolen vehicle alerts, etc.).

At 320, the method includes tracking the object/person having featuresthat match alert parameters with the scanning devices. For example, theobject/person may be monitored over time to track movements of theobject/person. From the movements, a heading and/or speed of theobject/person may be determined. At 322, the method includes determiningif the object/person is still detected by the scanning devices. If theobject/person is not still detected (e.g., “NO” at 322), the methodproceeds to 324 to transmit a last known location and/or heading/speedof the object/person to the alert service, and also to scan a regionselected based on the last known location/heading. The method may thenreturn to 310 to determine if the object/person is once again detected.If the object/person is still detected at 322 (e.g., “YES” at 322), themethod includes sending updates to the alert service at 326 (e.g.,regarding a changing location of the object/person), then returning tocontinue tracking the object/person with the scanning device(s).

FIG. 4 is a flow chart of an example method for group-based processingof an emergency alert using automatic alert processing systems (e.g.,examples of alert processing system 200 of FIG. 2) in multiple connectedvehicles. Method 400 may be performed by an automatic alert processingsystem (e.g., alert processing system 200 of FIG. 2) in one of aplurality of vehicles including such an alert processing system (e.g.,vehicle 104 b of FIGS. 1A-1C). At 402, the method includes receiving analert. At 404, the method includes identifying alert parameters. Forexample, the description of receiving an alert and identifying alertparameters provided for operations 302-306 of method 300 of FIG. 3 mayapply to the operations 402 and 404. Method 400 further includesscanning for objects and/or people matching the alert parameters. Thedescription of scanning for objects/people provided for operation 308 ofmethod 300 of FIG. 3 may apply to the operation 406 of method 400.

At 408, the method includes determining if an object and/or personmatching the alert parameters is detected. If an object and/or personmatching the alert parameters is detected (e.g., “YES” at 408), themethod proceeds to 410 and includes reporting to other vehicles (e.g.,via vehicle-to-vehicle communication) within a threshold distance of thevehicle performing method 400 that the object and/or person is detectedin the scanned region. The report may include an indication of theobject/person that was detected, features of the object/person that weredetected (e.g., features that match the alert parameters and/oradditional features that are not included in the alert parameters, whichmay further assist other vehicles in locating the object/person), alocation of the object/person (e.g., relative to the vehicle thatdetected the matching object/person and/or a location converted intoreal-world coordinates using known correspondences between vehicle-basedsensors and the real-world coordinate system), a time of detecting theobject/person, and/or other information. At 412, the method includescontinuing to track the object/person and returning to 408 to determineif the object/person is still detected.

If an object/person matching the alert parameters is not detected (e.g.,“NO” at 408), the method proceeds to 414 to report to the other vehiclesthat the object/person is not detected in the scanned region. At 416,the method includes determining if the alert processing system receives(e.g., from another vehicle, via vehicle-to-vehicle communication) anindication of an object/person detected by another vehicle. If the alertprocessing system does not receive an indication of an object/persondetected by another vehicle (e.g., “NO” at 416), the method returns to406 to continue scanning for objects/people that match the alertparameters. If the alert processing system does receive an indication ofan object/person detected by another vehicle (e.g., “YES” at 416), themethod includes targeting a scanning region based on the receivedindication at 418 and returning to 406 to scan for objects/peoplematching the alert parameters (e.g., in the targeted scanning region).In this way, information from surrounding vehicles may be used tocoordinate scanning amongst the neighboring vehicles.

FIG. 5 is a flow chart of an example method for distributing computingloads within one or more vehicle computing systems responsive to receiptof an emergency alert at an alert processing system of the vehicle.Method 500 may be performed by an automatic alert processing system(e.g., alert processing system 200 of FIG. 2) of a vehicle (e.g.,vehicle 104 b of FIGS. 1A-1C). At 502, the method includes receiving analert. At 504, the method includes identifying alert parametersincluding a target vehicle color. For example, the description ofreceiving an alert and identifying alert parameters provided foroperations 302-306 of method 300 of FIG. 3 may apply to the operations502 and 504. In the example method of 500, a target vehicle color isreferenced as an alert parameter included in the alert. However, it isto be understood that the operations of method 500 that reference avehicle color may be performed using any one or more alert parameters ofa received alert in addition to the vehicle color or as an alternativeto the vehicle color.

At 506, the method includes redirecting a first set of vehicle resourcesto scan for vehicles matching the target vehicle color. For example, afirst set of vehicle resources may include a first subset of cameras orother scanning devices (which may include some or all of thecameras/scanning devices mounted on the vehicle or otherwise availablefor use by the vehicle) and/or a portion of processing resources (e.g.,processing cores, processing logic units, memory, etc.). Redirection ofthe resources may include altering the operation of the devices, such asswitching the devices from off to on and/or switching processingresources from dormant to active, changing a directionality or otherscanning parameter of cameras/scanning devices, cancelling or holdingsome processing tasks to prioritize processing of scan data, etc. Insome examples, current usage of at least some of the first set ofvehicle resources (e.g., usage prior to the redirection of resources)may be maintained while still using the resources for scanningoperations. For example, cameras that are used for providing a surroundview of a vehicle to an in-vehicle display may still provide thesurround view, but captured data may also be forwarded to processingmodules for analyzing the captured data to scan for vehicles matchingthe alert parameters.

At 508, the method includes determining if a vehicle matching the targetvehicle color is found. If a vehicle matching the target vehicle coloris not found (e.g., “NO” at 508), the method optionally includesreducing resources used for scanning, as indicated at 510, and returnsto continue scanning for a vehicle matching the target vehicle color. Insome examples, resources used for scanning may be reduced by a setamount each time a vehicle that matches the target vehicle color is notfound, until insufficient resources are available for performing thescanning operation, at which point the method returns to wait for a newalert. In other examples, the resources used for scanning may be reducedup to a minimum amount in order to enable the system to continuescanning until a vehicle matching the target vehicle color is found orthe vehicle leaves a region associated with the alert (e.g., a region inwhich the alert was broadcast) or otherwise encounters a stop scanningcondition (e.g., the vehicle shuts off, a user stops the scanning,etc.). The first set of vehicle resources and/or the way in whichresources are reduced may be selected by user preference and/or selectedbased on a parameter of the alert (e.g., an urgency of the alert, thepresence of reports from neighboring vehicles that responded to thealert, etc.).

If a vehicle matching the target vehicle color is found (e.g., “YES” at508), the method includes redirecting a second set of vehicle resourcesto analyze features of the found vehicle, as indicated at 512. Thesecond set may be at least partially different from the first set, asindicated at 514, and/or the second set may be used in addition to thefirst set, as indicated at 516. In either case, the second set ofresources may be larger than the first set of resources. In someexamples, the first set of vehicle resources may include morecamera/scanning device resources than the second set of vehicleresources, while the second set of vehicle resources may include moreprocessing resources than the first set of vehicle resources. In thisway, at a first stage, a large amount of scanning data may be capturedfor a large area around the vehicle, and a minimal amount of processingmay be performed on the data to quickly locate vehicles matching a firstalert parameter (e.g., a vehicle color). At a second stage, the scanningresources may be targeted at a found vehicle (or at each found vehicleif multiple vehicles matching the target vehicle color are detected) andadditional processing resources may be applied to derive additionaldetails of the found vehicle(s) (e.g., performing license platescanning, identifying occupants of the vehicle(s), identifying location,speed, heading, appearance, and/or other features of the vehicle(s),etc.).

At 518, the method includes determining if other features of the foundvehicle and/or associated occupants match the alert parameters. If otherfeatures matching the alert parameters are not detected (e.g., “NO” at518), the method includes assigning the found vehicle a lowestlikelihood of a match (e.g., a lowest confidence score) at 520. If otherfeatures matching the alert parameters are detected (e.g., “YES” at518), the method includes assigning the found vehicle a likelihood of amatch (e.g., a confidence score) that is based on a number and/or typeof matches to the alert parameters, as indicated at 522. For example,some alert parameters may be weighed more heavily than others (e.g.,license plate parameters may be weighed more heavily than vehicle type,since there may be many vehicles of the same type on the road, butlicense plates are configured to be unique), such that heavily-weightedparameters increase a likelihood/confidence score more than other, lessheavily-weighted parameters. The likelihood/confidence score may alsoreflect a confidence in the analysis of scan data that lead to thedetermination of a match for each alert parameter.

At 524, the method includes transmitting information of the foundvehicle including a location, status, and/or assigned likelihood of amatch (e.g., confidence score) to other, neighboring vehicles and/or toan alert service. At 526, the method optionally includes continuing totrack the found vehicle. In some examples, the found vehicle may betracked using fewer resources than those used for detecting whether thefound vehicle matches alert parameters. In other examples, the foundvehicle may be tracked using the same or additional resources than thoseused for detecting whether the found vehicle matches alert parameters.In this way, the system may continuously adjust thelikelihood/confidence score based on ongoing tracking of the vehicle.

The disclosed methods and systems automatically process and respond toincoming alerts, such as AMBER alerts, using vehicle systems in order toattempt to locate objects and/or people described in the alerts. Atechnical effect of the disclosed methods and systems is that efficiencyand accuracy of responding to received alerts is increased relative tosystems in which alerts are presented to a user and responses aregenerated based only on user input. Vehicle scanning and processingresource redirection, as described with respect to FIG. 5, may alsoimprove the functioning of the vehicle systems by balancing processingand scanning loads according to priority assignments. Further resourcesavings may be achieved by leveraging information from neighboringvehicles to target scanning and data processing, as described withrespect to FIG. 4.

As described above, the example methods may be performed, at least inpart, within a vehicle using scanning systems and processing resourcesof the vehicle. FIG. 6 shows an example partial view of one type ofenvironment for an automatic alert processing system: an interior of acabin 600 of a vehicle 602, in which a driver and/or one or morepassengers may be seated. FIG. 6 may be an example of one or more ofvehicles 104 a-104 d of FIG. 1.

As shown, an instrument panel 606 may include various displays andcontrols accessible to a driver (also referred to as the user) ofvehicle 602. For example, instrument panel 606 may include a touchscreen 608 of an in-vehicle computing system 609 (e.g., an infotainmentsystem), an audio system control panel, and an instrument cluster 610.In some embodiments, one or more hardware elements of in-vehiclecomputing system 609, such as touch screen 608, a display screen,various control dials, knobs and buttons, memory, processor(s), and anyinterface elements (e.g., connectors or ports) may form an integratedhead unit that is installed in instrument panel 606 of the vehicle. Thehead unit may be fixedly or removably attached in instrument panel 606.In additional or alternative embodiments, one or more hardware elementsof the in-vehicle computing system may be modular and may be installedin multiple locations of the vehicle.

The cabin 600 may include one or more sensors for monitoring thevehicle, the user, and/or the environment. For example, the cabin 600may include one or more microphones to receive user input in the form ofvoice commands and/or to measure ambient noise in the cabin 600 oroutside of the vehicle (e.g., to establish a noise baseline forseparating siren sounds from environmental noise and/or to detect asiren sound), etc. Sensors for scanning the environment may include oneor more cameras, LiDAR arrays, and/or other optical sensors fordetecting features of the environment surrounding the vehicle. It is tobe understood that the above-described sensors and/or one or moreadditional or alternative sensors may be positioned in any suitablelocation of the vehicle. For example, sensors may be positioned in anengine compartment, on an external surface of the vehicle, and/or inother suitable locations for providing information regarding theoperation of the vehicle, ambient conditions of the vehicle, a user ofthe vehicle, etc. Information regarding ambient conditions of thevehicle, vehicle status, or vehicle driver may also be received fromsensors external to/separate from the vehicle (that is, not part of thevehicle system), such as sensors coupled to external devices 650 and/ormobile device 628.

Cabin 600 may also include one or more user objects, such as mobiledevice 628, that are stored in the vehicle before, during, and/or aftertravelling. The mobile device 628 may include a smart phone, a tablet, alaptop computer, a portable media player, and/or any suitable mobilecomputing device. The mobile device 628 may be connected to thein-vehicle computing system via communication link 630. Thecommunication link 630 may be wired (e.g., via Universal Serial Bus[USB], Mobile High-Definition Link [MHL], High-Definition MultimediaInterface [HDMI], Ethernet, etc.) or wireless (e.g., via BLUETOOTH,WIFI, WIFI direct Near-Field Communication [NFC], cellular connectivity,etc.) and configured to provide two-way communication between the mobiledevice and the in-vehicle computing system. The mobile device 628 mayinclude one or more wireless communication interfaces for connecting toone or more communication links. For example, the communication link 630may provide sensor and/or control signals from various vehicle systems(such as vehicle audio system, sensor subsystem, etc.) and the touchscreen 608 to the mobile device 628 and may provide control and/ordisplay signals from the mobile device 628 to the in-vehicle systems andthe touch screen 608. In some examples, the mobile device 628 mayprovide additional resources for performing scanning operations (e.g.,for scanning and/or for processing scanned data) and/or for negotiatingbetween vehicles (e.g., for negotiating communication parameters ormaster vehicle designations between vehicles).

In-vehicle computing system 609 may also be communicatively coupled toadditional devices operated and/or accessed by the user but locatedexternal to vehicle 602, such as one or more external devices 650. Inthe depicted embodiment, external devices are located outside of vehicle602 though it will be appreciated that in alternate embodiments,external devices may be located inside cabin 600. The external devicesmay include a server computing system, personal computing system,portable electronic device, electronic wrist band, electronic head band,portable music player, electronic activity tracking device, pedometer,smart-watch, GPS system, etc. External devices 650 may be connected tothe in-vehicle computing system via communication link 636 which may bewired or wireless, as discussed with reference to communication link630, and configured to provide two-way communication between theexternal devices and the in-vehicle computing system. For example,external devices 650 may include one or more sensors and communicationlink 636 may transmit sensor output from external devices 650 toin-vehicle computing system 609 and touch screen 608.

In-vehicle computing system 609 may analyze the input received fromexternal devices 650, mobile device 628, and/or other input sources andprovide output via touch screen 608 and/or speakers 612, communicatewith mobile device 628 and/or external devices 650, and/or perform otheractions based on the assessment. In some embodiments, all or a portionof the assessment may be performed by the mobile device 628 and/or theexternal devices 650. In some embodiments, the external devices 650 mayinclude in-vehicle computing devices of another vehicle (e.g., anothervehicle grouped with vehicle 602).

FIG. 7 shows a block diagram of an in-vehicle computing system 700configured and/or integrated inside vehicle 701. In-vehicle computingsystem 700 may be an example of in-vehicle computing system 609 of FIG.6 and/or may perform one or more of the methods described herein in someembodiments. In some examples, the in-vehicle computing system may be avehicle infotainment system configured to provide information-basedmedia content (audio and/or visual media content, includingentertainment content, navigational services, map data, etc.) to avehicle user to enhance the operator's in-vehicle experience. Thevehicle infotainment system may include, or be coupled to, variousvehicle systems, sub-systems, hardware components, as well as softwareapplications and systems that are integrated in, or integratable into,vehicle 701 in order to enhance an in-vehicle experience for a driverand/or a passenger.

In-vehicle computing system 700 may include one or more processorsincluding an operating system processor 714 and an interface processor720. Operating system processor 714 may execute an operating system onthe in-vehicle computing system, and control input/output, display,playback, and other operations of the in-vehicle computing system.Interface processor 720 may interface with a vehicle control system 730via an intra-vehicle communication module 722.

Intra-vehicle communication module 722 may output data to other vehiclesystems 731 and vehicle control elements 761, while also receiving datainput from other vehicle components and systems 731, 761, e.g. by way ofvehicle control system 730. When outputting data, intra-vehiclecommunication module 722 may provide a signal via a bus corresponding toany status of the vehicle, the vehicle surroundings (e.g., as measuredby one or more microphones, cameras, LiDAR systems, or other sensorsmounted on the vehicle), or the output of any other information sourceconnected to the vehicle. Vehicle data outputs may include, for example,analog signals (such as current velocity), digital signals provided byindividual information sources (such as clocks, thermometers, locationsensors such as Global Positioning System [GPS] sensors, etc.), anddigital signals propagated through vehicle data networks (such as anengine controller area network [CAN] bus through which engine relatedinformation may be communicated and/or an audio-video bridging [AVB]network through which vehicle information may be communicated). Forexample, the in-vehicle computing system may retrieve from the engineCAN bus the current speed of the vehicle estimated by the wheel sensors,a current location of the vehicle provided by the GPS sensors, and acurrent trajectory of the vehicle provided by one or more inertialmeasurement sensors in order to determine an estimated path of thevehicle (e.g., for updating a display of the in-vehicle computingsystem). In addition, other interfacing protocols/hardware such asEthernet or Bluetooth may be used as well without departing from thescope of this disclosure.

A non-volatile storage device 708 may be included in in-vehiclecomputing system 700 to store data such as instructions executable byprocessors 714 and 720 in non-volatile form. The storage device 708 maystore application data to enable the in-vehicle computing system 700 toperform any of the above-described methods and/or to run an applicationfor connecting to a cloud-based server and/or collecting information fortransmission to the cloud-based server. Connection to a cloud-basedserver may be mediated via extra-vehicle communication module 724. Theapplication may retrieve information gathered by vehiclesystems/sensors, input devices (e.g., user interface 718), devices incommunication with the in-vehicle computing system, etc. In-vehiclecomputing system 700 may further include a volatile memory 716. Volatilememory 716 may be random access memory (RAM). Non-transitory storagedevices, such as non-volatile storage device 708 and/or volatile memory716, may store instructions and/or code that, when executed by aprocessor (e.g., operating system processor 714 and/or interfaceprocessor 720), controls the in-vehicle computing system 700 to performone or more of the actions described in the disclosure.

A microphone 702 may be included in the in-vehicle computing system 700to measure ambient noise in the vehicle, to measure ambient noiseoutside the vehicle, etc. One or more additional sensors may be includedin and/or communicatively coupled to a sensor subsystem 710 of thein-vehicle computing system 700. For example, the sensor subsystem 710may include and/or be communicatively coupled to scanning sensorsincluding a LiDAR system and/or a camera system (e.g., a rear viewcamera, a front view camera, side view cameras, LiDAR sensors disposedto cover a 360 degree area around the vehicle, etc.). Sensor subsystem710 of in-vehicle computing system 700 may communicate with and receiveinputs from various vehicle sensors and may further receive user inputs.While certain vehicle system sensors may communicate with sensorsubsystem 710 alone, other sensors may communicate with both sensorsubsystem 710 and vehicle control system 730, or may communicate withsensor subsystem 710 indirectly via vehicle control system 730. Sensorsubsystem 710 may serve as an interface (e.g., a hardware interface)and/or processing unit for receiving and/or processing received signalsfrom one or more of the sensors described in the disclosure.

A navigation subsystem 711 of in-vehicle computing system 700 maygenerate and/or receive navigation information such as locationinformation (e.g., via a GPS sensor and/or other sensors from sensorsubsystem 710), route guidance, traffic information, point-of-interest(POI) identification, and/or provide other navigational services for thedriver. The navigation subsystem 711 may include an inertial navigationsystem that may further determine a position, orientation, and velocityof the vehicle via motion and rotation sensor inputs. The navigationsubsystem 711 may communicate with motion and rotation sensors includedin the sensor subsystem 710. Alternatively, the navigation subsystem 711may include motion and rotation sensors and determine the movement androtation based on the output of these sensors. Navigation subsystem 711may transmit data to, and receive data from a cloud-based server and/orexternal navigation service via extra-vehicle communication module 724.The navigation subsystem 711 may provide at least a portion of data tobe used during generation of a three-dimensional map of a region aroundthe vehicle in some examples.

External device interface 712 of in-vehicle computing system 700 may becoupleable to and/or communicate with one or more external devices 740located external to vehicle 701. While the external devices areillustrated as being located external to vehicle 701, it is to beunderstood that they may be temporarily housed in vehicle 701, such aswhen the user is operating the external devices while operating vehicle701. In other words, the external devices 740 are not integral tovehicle 701. The external devices 740 may include a mobile device 742(e.g., connected via a Bluetooth, NFC, WIFI direct, or other wirelessconnection) or an alternate Bluetooth-enabled device 752. Other externaldevices include external services 746. For example, the external devicesmay include extra-vehicular devices that are separate from and locatedexternally to the vehicle. Still other external devices include externalstorage devices 754, such as solid-state drives, pen drives, USB drives,etc. External devices 740 may communicate with in-vehicle computingsystem 700 either wirelessly or via connectors without departing fromthe scope of this disclosure. For example, external devices 740 maycommunicate with in-vehicle computing system 700 through the externaldevice interface 712 over network 760, a universal serial bus (USB)connection, a direct wired connection, a direct wireless connection,and/or other communication link.

One or more applications 744 may be operable on mobile device 742. As anexample, mobile device application 744 may be operated to monitor anenvironment of the vehicle (e.g., collect audio and/or visual data of anenvironment of the vehicle) and/or to process audio and/or visual datareceived from vehicle sensors. The collected/processed data may betransferred by application 744 to external device interface 712 overnetwork 760. Likewise, one or more applications 748 may be operable onexternal services 746. As an example, external services applications 748may be operated to aggregate and/or analyze data from multiple datasources. For example, external services applications 748 may aggregatedata from the in-vehicle computing system (e.g., sensor data, log files,user input, etc.), etc.

Vehicle control system 730 may include controls for controlling aspectsof various vehicle systems 731 involved in different in-vehiclefunctions. Vehicle control system 730 may also include controls foradjusting the settings of various vehicle controls 761 (or vehiclesystem control elements) related to the engine and/or auxiliary elementswithin a cabin of the vehicle.

In-vehicle computing system 700 may further include an antenna(s) 706,which may be communicatively coupled to external device interface 712and/or extra-vehicle-communication module 724. The in-vehicle computingsystem may receive positioning signals such as GPS signals and/orwireless commands via antenna(s) 706 or via infrared or other mechanismsthrough appropriate receiving devices.

One or more elements of the in-vehicle computing system 700 may becontrolled by a user via user interface 718. User interface 718 mayinclude a graphical user interface presented on a touch screen, such astouch screen 608 of FIG. 6, and/or user-actuated buttons, switches,knobs, dials, sliders, etc. For example, user-actuated elements mayinclude steering wheel controls, door and/or window controls, instrumentpanel controls, navigation system settings, and the like. A user mayalso interact with one or more applications of the in-vehicle computingsystem 700 and mobile device 742 via user interface 718. Notificationsand other messages (e.g., alerts), as well as navigational assistance(e.g., 3D maps), may be displayed to the user on a display of the userinterface.

The disclosure provides for an in-vehicle computing system of a vehicle,the in-vehicle computing system including a sensor subsystem incommunication with a sensor, a communication interface, a processor, andmemory storing instructions executable by the processor to receive, viathe communication interface, an alert including one or more alertparameters associated with one or more target objects, instruct thesensor to scan an assigned region around the vehicle, receive, from thesensor, locally scanned data corresponding to the assigned region,determine that the scanned data includes an object having featuresmatching a selected alert parameter of the one or more alert parameters,and transmit, to an alert service, a notification identifying the objectand the features matching the selected alert parameter, the notificationincluding a location of the object. In a first example of the in-vehiclecomputing system, the alert may additionally or alternatively include anemergency alert. A second example of the in-vehicle computing systemoptionally includes the first example, and further includes thein-vehicle computing system, wherein the selected alert parameterincludes a target color of a target vehicle. A third example of thein-vehicle computing system optionally includes one or both of the firstand second examples, and further includes the in-vehicle computingsystem, wherein the instructions are further executable to redirect afirst set of vehicle resources to determine that the scanned dataincludes a found vehicle having the target color, and to redirect asecond set of vehicle resources to determine additional features of thefound vehicle. A fourth example of the in-vehicle computing systemoptionally includes one or more of the first through the third examples,and further includes the in-vehicle computing system, wherein the firstset of vehicle resources includes a first set of optical sensorsscanning a first region around the vehicle, and the second set ofvehicle resources includes a second set of optical sensors scanning asecond region around the vehicle, the second region being smaller thanthe first region and selected based on a location of the found vehicle.A fifth example of the in-vehicle computing system optionally includesone or more of the first through the fourth examples, and furtherincludes the in-vehicle computing system, wherein the first set ofvehicle resources includes a first set of processing resources forperforming color matching, and wherein the second set of vehicleresources includes a second, larger set of processing resources fordetecting additional features of the found vehicle in addition to thetarget color. A sixth example of the in-vehicle computing systemoptionally includes one or more of the first through the fifth examples,and further includes the in-vehicle computing system, wherein theselected alert parameter includes one or more of a license plateidentification and a vehicle make and/or model indicating a vehicleshape. A seventh example of the in-vehicle computing system optionallyincludes one or more of the first through the sixth examples, andfurther includes the in-vehicle computing system, wherein the selectedalert parameter includes one or more features of a person of interest.An eighth example of the in-vehicle computing system optionally includesone or more of the first through the seventh examples, and furtherincludes the in-vehicle computing system, wherein the instructions arefurther executable to transmit, to one or more neighboring vehicles, thenotification identifying the object, the location of the object, and thefeatures of the object matching the selected alert parameter. A ninthexample of the in-vehicle computing system optionally includes one ormore of the first through the eighth examples, and further includes thein-vehicle computing system, wherein the notification further includes aconfidence score indicating a likelihood that the object matches one ofthe one or more target objects. A tenth example of the in-vehiclecomputing system optionally includes one or more of the first throughthe ninth examples, and further includes the in-vehicle computingsystem, wherein the instructions are further executable to receive, fromone or more neighboring vehicles, a report indicating a reportedlocation of a reported object matching the selected alert parameter, andwherein the assigned region around the vehicle is selected based on thereported location of the reported object as indicated in the report. Aneleventh example of the in-vehicle computing system optionally includesone or more of the first through the tenth examples, and furtherincludes the in-vehicle computing system, wherein the instructions arefurther executable to verify that the received alert is authentic beforeinstructing the sensor to scan the assigned region, and beforetransmitting the notification to the alert service. A twelfth example ofthe in-vehicle computing system optionally includes one or more of thefirst through the eleventh examples, and further includes the in-vehiclecomputing system, wherein the instructions are further executable todetermine additional contextual information regarding the objectmatching the selected alert parameter and transmit the additionalcontextual information with the notification. A thirteenth example ofthe in-vehicle computing system optionally includes one or more of thefirst through the twelfth examples, and further includes the in-vehiclecomputing system, wherein the additional contextual information includesone more of a heading of the object, a speed of the object, and a statusof the object, and/or wherein the additional contextual information isderived using measurements from one or more additional sensors incommunication with the sensor subsystem. A fourteenth example of thein-vehicle computing system optionally includes one or more of the firstthrough the thirteenth examples, and further includes the in-vehiclecomputing system, wherein the one or more additional sensors includesone or more of a sonar array and a radar array. In this way, one or moreof the alert parameters may be detected by a first sensor (e.g., anoptical sensor, such as a LiDAR sensor) and the additional contextualinformation may be detected by a second, different sensor or sensorarray (e.g., a sonar array and/or a radar array). A fifteenth example ofthe in-vehicle computing system optionally includes one or more of thefirst through the fourteenth examples, and further includes thein-vehicle computing system, wherein the additional contextualinformation includes one or more features of the object that are notassociated with the one or more alert parameters. A sixteenth example ofthe in-vehicle computing system optionally includes one or more of thefirst through the fifteenth examples, and further includes thein-vehicle computing system, wherein the alert includes an America'sMissing: Broadcast Emergency Response (AMBER) alert. A seventeenthexample of the in-vehicle computing system optionally includes one ormore of the first through the sixteenth examples, and further includesthe in-vehicle computing system, wherein the sensor is an opticalsensor.

The disclosure further provides for a method for responding to anincoming alert with an automatic alert processing system of a vehicle,the method including scanning an assigned region around a vehicle for anobject matching one or more alert parameters of the incoming alert, theone or more alert parameters describing one or more target objects, andtransmitting, to an alert service, a notification indicating a locationof a found object that matches at least a selected parameter of the oneor more alert parameters of the incoming alert, the notificationincluding a confidence score indicating a likelihood that the foundobject matches one or more target objects of the incoming alert. In afirst example of the method, the incoming alert may additionally oralternatively include an America's Missing: Broadcast Emergency Response(AMBER) alert received via one or more data paths. A second example ofthe method optionally includes the first example, and further includesthe method, wherein the one or more data paths includes a broadcasttransmission and a communication link between the vehicle and a mobilephone located in the vehicle, and wherein different alert parameters areprovided on different data paths of the one or more data paths, themethod including selecting the assigned region based on the one or morealert parameters.

The disclosure also provides for an in-vehicle computing system of avehicle, the in-vehicle computing system including a sensor subsystem incommunication with an optical sensor, a communication interface, aprocessor, and memory storing instructions executable by the processorto receive, via the communication interface, an alert including one ormore alert parameters associated with one or more target objects,instruct the optical sensor to scan a first assigned region around thevehicle, determine, using a first set of processing resources, thatscanned data corresponding to the first assigned region includes anobject having features matching a selected alert parameter of the one ormore alert parameters, instruct the optical sensor to scan a secondassigned region around the vehicle, the second assigned region beingsmaller than the first assigned region and targeting the object,determine, using a second set of processing resources analyzing scanneddata corresponding to the second assigned region, that the object hasadditional features matching one or more additional alert parameters ofthe one or more alert parameters, and transmit, to an alert service, anotification identifying the object and each of the features matchingeach associated alert parameter of the one or more alert parameters, thenotification including a location of the object. In a first example ofthe in-vehicle computing system, the notification may additionally oralternatively further include an indication of a confidence scoreindicating a likelihood that the object matches at least one of the oneor more target objects.

The description of embodiments has been presented for purposes ofillustration and description. Suitable modifications and variations tothe embodiments may be performed in light of the above description ormay be acquired from practicing the methods. For example, unlessotherwise noted, one or more of the described methods may be performedby a suitable device and/or combination of devices, such as thein-vehicle computing system 609 of FIG. 6 and/or the sensor subsystem710 of FIG. 7. The methods may be performed by executing storedinstructions with one or more logic devices (e.g., processors) incombination with one or more additional hardware elements, such asstorage devices, sensors, memory, hardware network interfaces/antennas,switches, actuators, clock circuits, etc. The described methods andassociated actions may also be performed in various orders in additionto the order described in this application, in parallel, and/orsimultaneously. The described systems are exemplary in nature, and mayinclude additional elements and/or omit elements. The subject matter ofthe present disclosure includes all novel and non-obvious combinationsand sub-combinations of the various systems and configurations, andother features, functions, and/or properties disclosed.

As used in this application, an element or step recited in the singularand proceeded with the word “a” or “an” should be understood as notexcluding plural of said elements or steps, unless such exclusion isstated. Furthermore, references to “one embodiment” or “one example” ofthe present disclosure are not intended to be interpreted as excludingthe existence of additional embodiments that also incorporate therecited features. The terms “first,” “second,” and “third,” etc. areused merely as labels, and are not intended to impose numericalrequirements or a particular positional order on their objects. Thefollowing claims particularly point out subject matter from the abovedisclosure that is regarded as novel and non-obvious.

The invention claimed is:
 1. An in-vehicle computing system of avehicle, the in-vehicle computing system comprising: a sensor subsystemin communication with a sensor; a communication interface; a processor;and memory storing instructions executable by the processor to: receive,via the communication interface, an alert including one or more alertparameters associated with one or more target objects; instruct thesensor to scan an assigned region around the vehicle; receive, from thesensor, locally scanned data corresponding to the assigned region;redirect a first subset of processing resources to monitor for objectsmatching a selected alert parameter of the one or more alert parametersin the locally scanned data; in a first condition: determine that thescanned data includes an object having a feature matching the selectedalert parameter, redirect a second subset of processing resources toanalyze and determine other features of the object, the second subset ofprocessing resources being larger than the first subset of processingresources, assign a confidence score to the object indicating alikelihood of a match of the object to the one or more target objectsbased on a number and/or type of matches to the one or more alertparameters, and transmit, to an alert service, a notificationidentifying the object, the feature matching the selected alertparameter, and the confidence score, the notification including alocation of the object; and in a second condition: determine that thescanned data does not include any object having features matching theselected alert parameter, and monitor for objects matching the selectedalert parameter of the one or more alert parameters in the locallyscanned data using a reduced amount of processing resources from thefirst subset of processing resources.
 2. The in-vehicle computing systemof claim 1, wherein the alert includes an emergency alert.
 3. Thein-vehicle computing system of claim 2, wherein the selected alertparameter includes a target color of a target vehicle.
 4. The in-vehiclecomputing system of claim 3, wherein the instructions are furtherexecutable to redirect a first set of vehicle resources to determinethat the scanned data includes a found vehicle having the target color,and to redirect a second set of vehicle resources to determineadditional features of the found vehicle.
 5. The in-vehicle computingsystem of claim 4, wherein the first set of vehicle resources includes afirst set of optical sensors scanning a first region around the vehicle,and the second set of vehicle resources includes a second set of opticalsensors scanning a second region around the vehicle, the second regionbeing smaller than the first region and selected based on a location ofthe found vehicle.
 6. The in-vehicle computing system of claim 1,wherein the first subset of processing resources includes a first set ofprocessing resources for performing color matching, and wherein thesecond subset of processing resources includes a second, larger set ofprocessing resources for detecting additional features of a foundvehicle in addition to a target color.
 7. The in-vehicle computingsystem of claim 1, wherein the selected alert parameter includes one ormore of a license plate identification and a vehicle make or modelindicating a vehicle shape, and wherein a match to the license plateidentification of the alert is weighed more heavily in a calculation ofthe confidence score than a match to the vehicle make or model of thealert.
 8. The in-vehicle computing system of claim 1, wherein theselected alert parameter includes one or more features of a person ofinterest, and wherein the assigned region is selected based on anindication input from a user regarding a reported object matching atleast one of the one or more alert parameters of the alert.
 9. Thein-vehicle computing system of claim 1, wherein the instructions arefurther executable to transmit, to one or more neighboring vehicles, thenotification identifying the object, the location of the object, and thefeature of the object matching the selected alert parameter.
 10. Thein-vehicle computing system of claim 9, wherein the notification furtherincludes the confidence score indicating the likelihood that the objectmatches one of the one or more target objects.
 11. The in-vehiclecomputing system of claim 1, wherein the instructions are furtherexecutable to receive, from one or more neighboring vehicles, a reportindicating a reported location of a reported object matching theselected alert parameter, and wherein the assigned region around thevehicle is selected based on the reported location of the reportedobject as indicated in the report.
 12. The in-vehicle computing systemof claim 1, wherein the instructions are further executable to verifythat the received alert is authentic before instructing the sensor toscan the assigned region, and before transmitting the notification tothe alert service.
 13. The in-vehicle computing system of claim 1,wherein the instructions are further executable to determine additionalcontextual information regarding the object matching the selected alertparameter and transmit the additional contextual information with thenotification.
 14. The in-vehicle computing system of claim 13, whereinthe additional contextual information includes one more of a heading ofthe object, a speed of the object, and a status of the object, whereinthe additional contextual information is derived using measurements fromone or more additional sensors in communication with the sensorsubsystem.
 15. The in-vehicle computing system of claim 14, wherein theone or more additional sensors includes one or more of a sonar array anda radar array.
 16. A method for responding to an incoming alert with anautomatic alert processing system of a vehicle, the method comprising:receiving, from one or more neighboring vehicles, a report indicating areported location of a reported object identified by the one or moreneighboring vehicles as matching one or more alert parameters of theincoming alert, the one or more alert parameters describing one or moretarget objects; scanning an assigned region around the vehicle for anobject matching at least a selected alert parameter of the one or morealert parameters of the incoming alert, the assigned region around thevehicle being selected based on the reported location of the reportedobject as indicated in the report; receiving, from a sensor, datacorresponding to the assigned region; redirecting a first subset ofprocessing resources to monitor for objects matching a selected alertparameter of the one or more alert parameters in the locally scanneddata; in a first condition: determining that the scanned data includesthe object having a feature matching the selected alert parameter,redirecting a second subset of processing resources to analyze anddetermine other features of the object, the second subset of processingresources being larger than the first subset of processing resources,assigning a confidence score to the object indicating a likelihood of amatch of the object to the one or more target objects based on a numberand/or type of matches to the one or more alert parameters, in a secondcondition: determining that the scanned data does not include any objecthaving features matching the selected alert parameter, and monitoringfor objects matching the selected alert parameter of the one or morealert parameters in the locally scanned data using a reduced amount ofprocessing resources from the first subset of processing resources; andtransmitting, via a communication interface of the vehicle, anotification to an alert service, the notification indicating a locationof a found object that matches at least the selected alert parameter ofthe one or more alert parameters of the incoming alert, the notificationincluding a confidence score indicating a likelihood that the foundobject matches the one or more target objects of the incoming alert. 17.The method of claim 16, wherein the incoming alert includes an America'sMissing: Broadcast Emergency Response (AMBER) alert received via one ormore data paths.
 18. The method of claim 17, wherein the one or moredata paths includes a broadcast transmission and a communication linkbetween the vehicle and a mobile phone located in the vehicle, andwherein different alert parameters are provided on different data pathsof the one or more data paths, the method including selecting theassigned region based on the one or more alert parameters.
 19. Anin-vehicle computing system of a vehicle, the in-vehicle computingsystem comprising: a sensor subsystem in communication with an opticalsensor and one or more additional scanning devices; a communicationinterface; a processor; and memory storing instructions executable bythe processor to: receive, via the communication interface, an alertincluding one or more alert parameters associated with one or moretarget objects; instruct a first subset of scanning resources of thesensor subsystem including the optical sensor to scan a first assignedregion around the vehicle; determine, using a first set of processingresources, that scanned data corresponding to the first assigned regionincludes an object having features matching a selected alert parameterof the one or more alert parameters; instruct a second subset ofscanning resources of the sensor subsystem to scan a second assignedregion around the vehicle, the second assigned region being smaller thanthe first assigned region and targeting the object, and the secondsubset of scanning resources including fewer scanning devices than thefirst subset of scanning resources; determine, using a second set ofprocessing resources analyzing scanned data corresponding to the secondassigned region, that the object has additional features matching one ormore additional alert parameters of the one or more alert parameters,the second set of processing resources including more processingresources than the first set of processing resources; and transmit, toan alert service, a notification identifying the object and each of thefeatures matching each associated alert parameter of the one or morealert parameters, the notification including a location of the object.20. The in-vehicle computing system of claim 19, wherein thenotification further includes an indication of a confidence scoreindicating a likelihood that the object matches at least one of the oneor more target objects, and wherein the first subset of scanningresources and/or the second subset of scanning resources is furtherbased on a report from another vehicle that a reported object matchingat least one alert parameter of the alert was identified, the firstsubset of scanning resources and/or the second subset of scanningresources being selected to include one or more scanning devices of thesensor subsystem that are positioned on a selected side of the vehicle,the selected side being selected based on an estimated approachdirection of the reported object.